Industrial internet of things system for automatic replacement of production line production devices and control methods thereof

ABSTRACT

Disclosed herein are an industrial internet of things system for automatic replacement of production line production devices and control methods thereof. The industrial internet of things system comprises: a user platform, a service platform, a management platform, a sensor network platform, and an object platform. The second server determines, based on a matching relationship between the at least one redundant device and the working devices, replaceable candidate redundant devices corresponding to the working devices when receiving an instruction for producing a new product transmitted by the first server, and determines a replacement scheme based on the replaceable candidate redundant devices, wherein the instruction is obtained from the terminal and the replacement scheme including replaceable target redundant devices corresponding to the working devices; generates a replacement instruction based on the replacement scheme, and sends the replacement instruction to the working devices and the corresponding target redundant devices of the object platform.

CROSS REFERENCE TO RELATED APPLICATION

This application is a Continuation of U.S. patent application Ser. No.17/806,738 filed on Jun. 14, 2022, the contents of which areincorporated herein by reference.

TECHNICAL FIELD

The present disclosure relates to intelligent manufacturing technology,in particular to industrial internet of things system for automaticreplacement of production line production devices and control methods.

BACKGROUND

Industrial intelligent manufacturing technology has developed on a largescale, but the research on industrial intelligent manufacturingtechnology basically stays in the research of underlying technology,such as how to realize relevant requirements in the application ofspecific projects, which makes the applicability of intelligentmanufacturing technology generally poor and easy to cause repeateddevelopment. At the same time, in the existing technology, the controlcalculation of industrial intelligent manufacturing technology and thecommunication network in the factory are often constructed uniformly,and all the communication calculation pressure is gathered in thetransmission control center, resulting in a large load in thetransmission control center and data traffic jam.

SUMMARY

The technical problem to be solved in the present disclosure is that thecalculation pressure of the intelligent manufacturing technology in theexisting technology is gathered in the transmission control center,resulting in a large load in the transmission control center and proneto data traffic jam. The purpose is to provide an industrial internet ofthings for automatic replacement of production line production devicesand control methods thereof to solve the above problems.

The present disclosure is realized through the following technicalschemes.

On one hand, the present disclosure provides an industrial internet ofthings system for automatic replacement of production line productiondevices, comprising:

-   -   a user platform, a service platform, a management platform, a        sensor network platform, and an object platform that interact in        turn; wherein: the user platform is configured as a terminal        device and interacts with a user;    -   the service platform is configured as a first server, receives        an instruction of the user platform and sends it to the        management platform, extracts information required for        processing the user platform from the management platform, and        sends the information to the user platform;    -   the management platform is configured as a second server,        controls the operation of the object platform, and receives        feedback data from the object platform;    -   the sensor network platform is configured as a communication        network and a gateway for the interaction between the object        platform and the management platform;    -   the object platform is configured as production line devices,        the production line devices including a plurality types of        production devices arranged in a preset order, each of the        plurality types of production devices including a plurality of        working devices and at least one redundant device;    -   the second server determines, based on a matching relationship        between the at least one redundant device and the working        devices, replaceable candidate redundant devices corresponding        to the working devices when receiving an instruction for        producing a new product transmitted by the first server, and        determines a replacement scheme based on the replaceable        candidate redundant devices, wherein the instruction is obtained        from the terminal and the replacement scheme including        replaceable target redundant devices corresponding to the        working devices;    -   the second server generates a replacement instruction based on        the replacement scheme, and sends the replacement instruction to        the working devices and the corresponding target redundant        devices of the object platform.

On the other hand, the embodiment of the present disclosure provides acontrol method of the industrial internet of things system for automaticreplacement of production line production devices, applied to a userplatform, a service platform, a management platform, a sensor networkplatform, and an object platform that interact in turn, wherein:

-   -   the user platform is configured as a terminal device and        interacts with a user;    -   the service platform is configured as a first server, receives        an instruction of the user platform and sends it to the        management platform, extracts information required for        processing the user platform from the management platform, and        sends the information to the user platform;    -   the management platform is configured as a second server,        controls the operation of the object platform, and receives        feedback data from the object platform;    -   the sensor network platform is configured as a communication        network and a gateway for the interaction between the object        platform and the management platform;    -   the object platform is configured as production line devices,        the production line devices including a plurality types of        production devices arranged in a preset order, each of the        plurality types of production devices including a plurality of        working devices and at least one redundant device;    -   the control method comprises:    -   determining, by the second server, replaceable candidate        redundant devices corresponding to the working devices based on        a matching relationship between the at least one redundant        device and the working devices when receiving an instruction for        producing a new product transmitted by the first server, and        determining a replacement scheme based on the replaceable        candidate redundant devices, wherein the instruction is obtained        from the terminal and the replacement scheme including        replaceable target redundant devices corresponding to the        working devices;    -   generating, by the second server, a replacement instruction        based on the replacement scheme, and sends the replacement        instruction to the working devices and the corresponding target        redundant devices of the object platform.

Compared with the prior art, the present disclosure has the followingadvantages and beneficial effects.

The industrial internet of things with an independent sensor networkplatform and control method in the present disclosure adopt thefive-platform structure proposed by the inventor to build theintelligent manufacturing internet of things, in which each platform hascorresponding hardware equipment. Because the service platform andmanagement platform are centralized, and the sensor network platform isindependent, in this way, the original unified sensor network platformhas formed many independent communication networks. The gateway on eachcommunication network can share part of the calculation for themanagement platform, effectively reducing the computing pressure of themanagement platform. Different communication networks are independent ofeach other, and also ensuring data security.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings described herein are used to provide a furtherunderstanding of the embodiments of the present disclosure, constitute apart of the present disclosure, and do not constitute a limitation ofthe embodiments of the present disclosure. In the attachment:

FIG. 1 is a schematic diagram of the architecture of the Embodiments ofthe present disclosure;

FIG. 2 is a schematic diagram of steps of the method of the Embodimentsof the present disclosure;

FIG. 3 is a flowchart illustrating an exemplary process for controllingthe production process by industrial internet of things according tosome embodiments of the present disclosure;

FIG. 4 is a flowchart illustrating an exemplary process for determininga loading plan and sending a loading instruction by a sensor networkplatform according to some embodiments of the present disclosure.

DETAILED DESCRIPTION

In order to make the purpose, technical scheme and advantages of thepresent disclosure clearer, the following is a further detaileddescription of the present disclosure in combination with theembodiments and drawings. The schematic embodiments and descriptions ofthe present disclosure are only used to explain the present disclosureand are not used as a limitation of the present disclosure. Theterminology used herein is for the purpose of describing particularexample embodiments only and is not intended to be limiting. As usedherein, the singular forms “a,” “an,” and “the” may be intended toinclude the plural forms as well, unless the context clearly indicatesotherwise, and the plural forms may be intended to include the singularform unless the context clearly indicates otherwise.

Embodiments

In order to facilitate the description of the above industrial internetof things with an independent sensor network platform, please refer toFIG. 1 , providing the schematic diagram of the communicationarchitecture of industrial internet of things with an independent sensornetwork platform disclosed in the Embodiment of the present disclosure.The industrial internet of things with an independent sensor networkplatform may include a user platform, a service platform, a managementplatform, a sensor network platform, and an object platform thatinteract in turn.

The user platform is configured as a terminal device and interacts witha user.

The service platform is configured as a first server, receives aninstruction of the user platform and sends it to the managementplatform, extracts information required for processing the user platformfrom the management platform, and sends the information to the userplatform.

The management platform is configured as a second server, controls theoperation of the object platform, and receives feedback data from theobject platform.

The sensor network platform is configured as a communication network anda gateway for the interaction between the object platform and themanagement platform.

The object platform is configured as production line devices andproduction line sensors that perform manufacturing.

The service platform and the management platform adopt a centralizedlayout, and the sensor network platform adopts an independent layout;the centralized layout refers to that a platform uniformly receivesdata, uniformly processes data and/or uniformly sends data; theindependent layout refers to a platform adopts different sub-platformsfor data storage, data processing, and/or data transmission fordifferent types of data.

The production line devices and the production line sensors of theobject platform are classified into a plurality of types according to anupstream and downstream relationship of an assembly line, each type, asan object sub-platform, corresponds to a sensor network sub-platform ofthe sensor network platform, and each sensor network sub-platformincludes an independent information channel and database; the databaseof each sensor network sub-platform is configured in the gateway; eachobject sub-platform corresponds to each sensor network sub-platform.

The second server classifies a control instruction according to the typeof the production line devices and the production line sensors of theobject platform to generate a classification control instruction whenreceiving the control instruction transmitted by the first server.

The second server generates different types of configuration filesaccording to the classification control instruction, and sends theconfiguration files to the databases of the sensor network sub-platformscorresponding to the types of configuration files, respectively.

Each sensor network sub-platform sends the configuration file in thedatabase to the production line device and a production line sensor ofthe corresponding object sub-platform through a correspondinginformation channel, respectively.

In the specific embodiment, the user platform may be a desktop computer,tablet computer, notebook computer, mobile phone or other electronicdevice that can realize data processing and data communication, which isnot limited here.

In the specific embodiment, the first server and the second server mayadopt a single server or a server cluster, which is not limited here. Itshould be understood that the data processing process mentioned in theembodiment of the present disclosure may be processed by the processorof the server, and the data stored in the server may be stored on thestorage device of the server, such as a hard disk and other memory.

In the specific embodiment, the gateway device of the sensor networkplatform in this embodiment should be an intelligent device with basicdata processing, timing processing, and other functions, and should alsohave the functions of data storage and data transmission.

During the implementation of this embodiment, the five-platformstructure proposed by the inventor is used to build the intelligentmanufacturing internet of things, in which each platform hascorresponding hardware device. Because the service platform andmanagement platform adopt a centralized layout, and the sensor networkplatform adopts an independent layout, the original unified sensornetwork platform forms many independent communication networks. Thegateway on each communication network may share part of the calculationfor the management platform, which effectively reduces the calculationpressure of the management platform, and different communicationnetworks are independent of each other, which also ensures the datasecurity.

In this embodiment, the devices in the object platform are divided intoa plurality of types according to the upstream and downstreamrelationship of the assembly line, each type has a special informationchannel and gateway, and the gateway is configured with a processor anda memory for storing the database. For example, if it is a hotprocessing production line, there are several types of devices accordingto the upstream and downstream relationship, which include devices forsubstrate placement, component assembly, solder spraying, reflow weldingmachine, and cooling. At this time, each type of device corresponds to aspecial information channel and gateway without interference with eachother.

According to the above classification relationship, the second serverclassifies the control commands received each time and generatescorresponding configuration files, each configuration file is sent bythe second server to the corresponding sensor network sub-platform. Inthis way, if the configuration file itself has requirements such astimeliness, this part of the calculation may be transferred to thesensor network platform for calculation, so as to reduce the resourceconsumption of the second server, and thus, this method is very suitablefor production lines with many links (stages).

In one embodiment, when configuration files corresponds to differentexecution times, the second server writes the execution times into thecorresponding configuration files.

When the database of the sensor network sub-platform receives and storesthe configuration file, the processor of the sensor network sub-platformextracts the execution time and sends the configuration file to theproduction line device and production line sensor in the correspondingobject sub-platform according to the execution time; the processor ofthe sensor network sub-platform is configured in the gateway.

During the implementation of this embodiment, when the production deviceexecutes the configuration file, it is generally necessary to be shutdown and read the configuration file, this process may face differentexecution times for different parts of the device. If this step isexecuted on the second server, many threads are required to monitor thedistribution time of these configuration files, and these threads cannothang in the background in the form of blocking, it will seriously occupyother control resources; in this embodiment, the time of sending theconfiguration file to the specific device is controlled and processed bythe processor of the sensor network platform, for the second server, itonly needs to complete the distribution of the configuration filewithout listening to the time corresponding to the configuration file,which reduces the count of threads wasted in this part.

In one embodiment, further, when the second server receives the controlinstruction transmitted by the first server, it obtains the productionline device and production line sensor in the object sub-platformcorresponding to the control instruction as the object device.

If the object device is configured with redundant devices, the secondserver sends the configuration file to the corresponding object devicethrough the corresponding sensor network sub-platform.

The second server sends a start instruction to the redundant devicethrough the sensing network sub-platform corresponding to the redundantdevice to start the redundant device, and the redundant device replacesthe work of the object device in the production line.

The object device accesses the production line and shutdown theredundant device after the configuration file is loaded.

During the implementation of this embodiment, the inventor found that inthe prior art, many production lines will cause huge losses if they areshut down, such as wafer production line, so these production linesoften set redundant devices for many key parts to replace these deviceswhen the production line devices fails. In view of this situation, thisembodiment sets corresponding communication channel and gateway forredundant device and object device respectively. When sending theconfiguration file, the redundant device takes over the work of theobject device, the object device loads a new configuration file, andthen the object device takes over the work of the redundant device,realizing the uninterrupted work of the production line.

In one embodiment, if the object device is configured with the redundantdevice, the second server obtains the startup time difference betweenthe object device and the redundant device; the startup time differenceis the time required for any one of the object device and the redundantdevice to start and take over the other;

-   -   the second server establishes a shutdown time and startup time        of the object device as a first time according to the startup        time difference, and establishes the startup time and shutdown        time of the redundant device as a second time according to the        startup time difference.

The second server packs the first time into the configuration file toform a first configuration file, and sends the first configuration fileto the database of the sensor network sub-platform corresponding to theobject device; the second server packs the second time into theconfiguration file to form a second configuration file, and sends thesecond configuration file to the database of the sensor networksub-platform corresponding to the redundant device.

The processor of the sensor network sub-platform sends the firstconfiguration file to the object device according to the first time; theobject device loads the first configuration file and is started up andshut down according to the first time.

The processor of the sensor network sub-platform sends the secondconfiguration file to the redundant device according to the second time;the redundant device loads the second configuration file and is startedup and shut down according to the second time.

As explained in the previous embodiment, the redundant device and thetarget device need to make two handover of work, so the time needs to bestrictly controlled, therefore, in this embodiment, the second servercompletes the establishment of time based on the startup timedifference; it should be understood that those skilled in the art shouldbe clear that the relationship between the first time and the secondtime is determined by the startup time difference. The second servercontrols the startup and shutdown time of the object device andredundant device by establishing the first time and the second time.

Before starting the redundant device, the second configuration fileneeds to be loaded, at this time, the processor of the sensor networkplatform sends the second configuration file according to the secondtime to realize the control, so that the configuration files of theredundant device and the object device may always be consistent.

In the second embodiment, the second server obtains an associated deviceof the object device if the object device is not configured with theredundant device; the associated device is the affected production linedevice and production line sensor of object platform which are locatedat the upstream of the object device when the object device is shutdown.

The second server obtains a loading time of the object device, andestablishes the shutdown time and startup time of the object device as athird time according to the loading time; the loading time is the timefrom being shut down to started up when the object device loads theconfiguration file.

The second server establishes the shutdown time and startup time of theassociated device as a fourth time according to the loading time.

The second server packs the third time into the configuration file toform a third configuration file, and sends the third configuration fileto the database of the sensor network sub-platform corresponding to theobject device.

The processor of the sensor network sub-platform sends the thirdconfiguration file to the object device according to the third time; theobject device loads the third configuration file and is shut down andstarted up according to the third time.

The second server sends the fourth time to the database of the sensornetwork sub-platform corresponding to the associated device.

The processor of the sensor network sub-platform sends the shutdowninstruction and the startup instruction to the associated deviceaccording to the fourth time.

The associated device is shut down according to the shutdown instructionand started up according to the startup instruction.

Different from the previous embodiment, in this embodiment, the targetdevice is not set with corresponding redundant device, at this time, itis necessary to stop the production line to load the configuration file,at this time, select the device related to the target device as theassociated device. The selection method of the associated device may berealized by using the device association table, which is used tocharacterize the upstream and downstream relationship and associationrelationship of each device. In other words, when the target device isto be shut down, its corresponding associated device must be shut down.Through this selection method, the third time and the fourth time aredetermined by the loading time, similarly, in this embodiment, theprocessor in the sensor network platform is also used for time control,and the second server is used to calculate and generate the specifictime, this method can effectively improve the update efficiency of theconfiguration file on the production line.

In some embodiments, the production process of the production deviceincludes a production process of a plurality types of production devicesarranged in a preset order to produce products, and each of theplurality types of production devices includes a plurality of workingdevices and at least one redundant device. The management platform mayreceive an instruction to produce a new product from the user platform.In response to the instruction, the management platform may determine areplaceable candidate redundant device corresponding to the workingdevice based on a matching relationship between the at least oneredundant device and the working device. The management platform maydetermine a replacement scheme based on the replaceable candidateredundant device corresponding to the working device. The replacementscheme may include a replaceable target redundant device correspondingto the working device. The management platform may send a replacementinstruction to the working device in the object platform and itscorresponding target redundant device based on the replacement scheme.

In some embodiments, the management platform may determine the count ofthe candidate redundant device corresponding to the working device. Themanagement platform may determine the replacement priority of workingdevice based on the count of candidate redundant device corresponding toworking device. The management platform may determine the replacementscheme based on the priority of replacement.

In some embodiments, the management platform may perform weightedsummation to determine the count of candidate redundant device based ontaking the loading success rate of each candidate redundant device asthe weight.

In some embodiments, in response to the count of the candidate redundantdevice corresponding to the working device is the same, the managementplatform may determine the replacement priority of the working devicebased on the loading success rate of each candidate redundant device.

In some embodiments, in response to when the count of candidateredundant device corresponding to the working device is the same, themanagement platform may determine the priority based on the upstreamdevice of the working device and the predicted loading completion time.The management platform may determine the replacement priority ofworking device based on priority.

In some embodiments, the management platform may obtain the confidenceof the predicted loading duration corresponding to the predicted loadingcompletion time. In response to the predicted loading duration isgreater than the threshold, the management platform may determine thepriority based on the predicted loading duration.

In some embodiments, the replacement scheme is carried out by aplurality of rounds of iteration.

In some embodiments, the sensor network platform may predict thepredicted loading time of the parameters (or predicted parameter loadingtime) of each type of production device for producing a new product. Thesensor network platform may determine the loading plan of redundantdevice based on the predicted loading time. The loading plan includesthe loading start time point (or start time point of the loading) ofeach device in each type of production devices. The sensor networkplatform may send loading instruction to the redundant device of theobject platform based on the loading plan.

The sensor network platform may determine a loading plan of theredundant device based on the predicted loading time, and the loadingplan includes a start time point of loading of each device of each typeof production devices.

In some embodiments, an input of the prediction model also includes theactual loading time of other production device that has been loaded.

In some embodiments, the sensor network platform may include a pluralityof sensor network sub-platforms. Each sensor network sub-platform of theplurality of sensor network sub-platforms corresponds to each type ofproduction devices, respectively. Each sensor network sub-platform isused to control the parameter loading of the corresponding productiondevice(s).

In some embodiments, the object platform may include a plurality ofobject sub-platforms, and each object sub-platform in the plurality ofobject sub-platforms corresponds to each type of production devices,respectively.

On the basis of the above, please refer to FIG. 2 , a flowchartillustrating the control method of the industrial internet of thingswith an independent sensor network platform provided by the embodimentsof the present disclosure. The control method of the industrial internetof things with an independent sensor network platform may be applied tothe system of the industrial internet of things with an independentsensor network platform in FIG. 1 . Further, the control method of theindustrial internet of things with an independent sensor networkplatform may specifically include the contents described in thefollowing steps S1 to S3.

S1: the second server classifies a control instruction according to atype of a production line device and a type of a production line sensorof the object platform and generates a classified control instructionwhen the second server receives a control instruction transmitted by thefirst server;

S2: the second server generates different types of configuration filesaccording to the classification control instruction (or classifiedcontrol instruction), and sends the configuration files to the databaseof the sensor network sub-platforms corresponding to the types ofconfiguration files;

S3: the sensor network sub-platform sends the configuration files in thedatabase to the production line devices and production line sensors inthe corresponding object sub-platforms through the correspondinginformation channels.

In one embodiment, when the configuration files correspond to differentexecution times, the second server writes the execution times into thecorresponding configuration files.

The processors of the sensor network sub-platforms extract the executiontimes and send the configuration files to the production line devicesand the production line sensors in the corresponding objectsub-platforms according to the execution times when the database of thesensor network sub-platforms receive and store the configuration files,respectively; the processors of the sensor network sub-platform areconfigured in the gateway.

In one embodiment, the second server obtains a production line deviceand a production line sensor in an object sub-platform corresponding tothe control instruction as an object device when receiving the controlinstruction transmitted by the first server.

The second server sends a configuration file to the corresponding objectdevice through the corresponding sensor network sub-platform if theobject device is configured with a redundant device.

The second server sends a start instruction to the redundant device tostart the redundant device, and the redundant device replaces the objectdevice to work in the production line.

The object device accesses the production line and closes the redundantdevice after loading the configuration file.

In one embodiment, the second server obtains the startup time differencebetween the object device and the redundant device if the object deviceis configured with a redundant device; the startup time difference isthe time period required for any one of the object device and theredundant device to start and take over the other one.

The second server establishes a shutdown time and startup time of theobject device as a first time according to the startup time difference,and establishes the startup time and shutdown time of the redundantdevice as a second time according to the startup time difference.

The second server packs the first time into the configuration file toform a first configuration file, and sends the first configuration fileto the database of the sensor network sub-platform corresponding to theobject device; the second server packs the second time into theconfiguration file to form a second configuration file, and sends thesecond configuration file to the database of the sensor networksub-platform corresponding to the redundant device.

The processor of the sensor network sub-platform sends the firstconfiguration file to the object device according to the first time; theobject device is started up, loads the first configuration file, and isshut down according to the first time.

The processor of the sensor network sub-platform sends the secondconfiguration file to the redundant device according to the second time;the redundant device loads the second configuration file and is startedup and according to the second time.

In one embodiment, the second server obtains an associated device of theobject device if the object device is not configured with a redundantdevice; the associated device is the affected production line devicesand production line sensors of object platform which are locatedupstream of the object device when the object device is shut down.

The second server obtains a loading time of the object device, andestablishes the shutdown time and startup time of the object device as athird time according to the loading time; the loading time is the timeperiod from being shut down to started up when the object device loadsthe configuration file.

The second server establishes the shutdown time and startup time of theassociated device as the fourth time according to the loading time.

The second server packs the third time into the configuration file toform a third configuration file, and sends the third configuration fileto the database of the sensor network sub-platform corresponding to theobject device.

The processor of the sensor network sub-platform sends the thirdconfiguration file to the object device according to the third time; theobject device loads the third configuration file and is shut down andstarted up according to the third time.

The second server sends the fourth time to the database of the sensornetwork sub-platform corresponding to the associated device.

The processor of the sensor network sub-platform sends the shutdowninstruction and the startup instruction to the associated deviceaccording to the fourth time.

The associated device is shut down according to the shutdown instructionand started up according to the startup instruction.

FIG. 3 is a flowchart illustrating an exemplary process for controllingthe production process by the internet of things according to someembodiments of the present disclosure. As shown in FIG. 3 , the process300 includes the following steps. In some embodiments, the process 300may be executed by the management platform.

In some embodiments, in a production line, various types of productiondevices may be arranged according to different production links orprocesses during the production of products by the production line. Theproduction process of production devices may have a sequence. Aplurality types of production devices may be arranged according to thepreset order to produce products. Each of a plurality type of productiondevices may include a plurality of working devices and one or moreredundant devices. The working device may refer to a device inproduction. The redundant device may refer to a spare device. Theredundant device may replace the working device for work when theworking device fails to work normally (such as abnormalities,replacement, etc.) to maintain the continuous operation of theproduction line and reduce the time of parameter loading.

In step 310, the management platform receives an instruction ofproducing a new product from the user platform.

When the production line needs to produce new products, thespecifications and requirements of new products are different, and theproduction device of the production line needs to adjust parameters. Theproduction device may load the production parameters of new products. Insome embodiments, the management platform may receive instructions toproduce new products from the user platform. For example, the userinputs the instruction of producing new products through the userplatform, and the instruction may be that production line 1 starts toproducing new product A. The management platform may receive theuser-input's instruction to produce new product A from the userplatform.

In step 320, in response to the instruction, the management platformdetermines a replaceable candidate redundant device corresponding to aworking device based on the matching relationship between at least oneredundant device and the working devices.

The matching relationship may refer to whether the redundant device ismatched with the working device. For example, whether the model matches,whether the location is close, etc. The candidate redundant devicerefers to a redundant device that meets the matching relationship withthe working device, for example, a redundant device that matches themodel of the working device.

In some embodiments, the management platform may determine replaceablecandidate redundant devices corresponding to the working devices basedon the matching relationship between one or more redundant devices andthe working devices. For example, working device 1 matches redundantdevices A and C, and working device 2 matches redundant device B. Themanagement platform may determine redundant devices A and C asreplaceable candidate redundant devices corresponding to working device1. The management platform may determine the redundant device B as areplaceable candidate redundant device corresponding to the workingdevice 2.

In step 330, the management platform determines a replacement schemebased on the replaceable candidate redundant device corresponding to theworking device, the replacement scheme including a replaceable targetredundant device corresponding to the working device.

The replacement scheme may refer to the specific contents of how toreplace the device. In some embodiments, the replacement scheme mayinclude a replaceable target redundant device corresponding to theworking device, replacement time, replacement priority, etc.

The target redundant device corresponding to the working device mayrefer to a determined final candidate redundant device that may replacethe working device. For example, as described in the above example, thereplaceable target redundant device corresponding to the working device1 may be redundant device A. The replaceable target redundant devicecorresponding to working device 2 may be redundant device B.

The management platform may determine the replacement scheme in aplurality of ways. In some embodiments, the replacement scheme may bedetermined based on the loading success rate of the candidate redundantdevice corresponding to the working device. For example, the loadingsuccess rates of redundant devices A, B and C are 90%, 85% and 80%,respectively. The management platform may determine a candidateredundant device with relatively high loading success rate as a targetredundant device. The management platform may preferentially replace theworking device corresponding to the candidate redundant device with highloading success rate. The replacement scheme determined by themanagement platform is as follows: the replaceable target redundantdevice corresponding to working device 1 is A; the replaceable targetredundant device corresponding to working device 2 is B; and thereplacement priority is to replace working device 1 first, and thenreplace working device 2, etc.

In some embodiments, the management platform may determine a count ofcandidate redundant devices corresponding to the working device. Themanagement platform may determine the replacement priority of workingdevice based on the count of candidate redundant devices correspondingto working device. The management platform may determine the replacementscheme based on the replacement priority.

The count of candidate redundant devices corresponding to the workingdevice may refer to the count of candidate redundant devices matchedwith the working device. The count of candidate redundant devicescorresponding to different working devices may be the same or different.For example, the count of candidate redundant devices corresponding toworking device 3 and working device 4 are 4 and 3, respectively.

In some embodiments, the management platform may determine the count ofcandidate redundant devices corresponding to the working device. Forexample, t the management platform may determine candidate redundantdevices matched with different working devices, thereby determining thecount of candidate redundant devices corresponding to different workingdevices. For example, through matching, the management platform maydetermine that the count of candidate redundant devices corresponding towork device 1, work device 2, work device 3 and work device 4 are 2, 1,4 and 3, respectively. In some embodiments, the candidate redundantdevices corresponding to different working devices may be the samecandidate redundant device. For example, candidate redundant device Emay match both working device 3 and working device 4.

The replacement priority of the working device may refer to the order inwhich the working device loads new product parameters. For example, thereplacement priority of the work device is work device 2, work device 3,work device 4, work device 1, etc. The work devices may load the newproduct parameters of the working devices according to the abovereplacement priority.

In some embodiments, the management platform may determine thereplacement priority of the working device based on the count ofcandidate redundant devices corresponding to the working device. Forexample, the management platform may sort the count of candidateredundant devices corresponding to the working device from small tolarge. The management platform may preferentially replace the workingdevice corresponding to a small count of candidate redundant devices. Asdescribed in the above example, the replacement priority of work device1 to work device 4 are in the following: work device 2 (thecorresponding count is 1), work device 1 (the corresponding count is 2),work device 4 (the corresponding count is 3), and work device 3 (thecorresponding count is 4).

In some embodiments, the management platform may determine a replacementscheme based on the replacement priority. For example, as described inthe above example, the corresponding scheme is as follows: thereplacement priority is that the working device 2 is replaced inpreference to the working device 1, which is replaced in preference tothe working device 4, which is replaced in preference to the workingdevice 3.

In some embodiments of the present disclosure, the management platformmay preferentially replace the working device corresponding to a smallcount of candidate redundant devices, avoiding the correspondingcandidate redundant devices replacing other working devices, andavoiding that no candidate redundant device may replace the workingdevice corresponding to a small count of candidate redundant devices.

In some embodiments, the management platform may determine the count ofcandidate redundant devices by weighted summation based on the loadingsuccess rate of each candidate redundant device as the weight.

The loading success rate may refer to the probability that a devicesuccessfully loads parameters. In some embodiments, the managementplatform may determine the loading success rate according to thehistorical loading record statistics of each candidate redundant device.For example, the candidate redundant device F has 20 history loadingrecords, the count of successful loading is 16, and the loading successrate of the candidate redundant device F is 80%.

In some embodiments, the management platform may determine the count ofcandidate redundant devices corresponding to the working device byweighted summation based on the loading success rate of each candidateredundant device as the weight. For example, there are three candidateredundant devices corresponding to working device 4, and thecorresponding loading success rates are 50%, 80% and 90%, respectively.The count of working device candidates is 1.80%*2.2%*1.50%*2.2%. Foranother example, there are two candidate redundant devices correspondingto working device 1, and the corresponding loading success rates are 70%and 90% respectively. The count of candidate redundant devicecorresponding to working device 1 is 1.6 (1*70%+1*90%=1.6).

In some embodiments, the management platform may preset a loadingsuccess rate threshold. The management platform may determine the countof candidate redundant devices corresponding to the working device basedon the loading success rate threshold. The loading success ratethreshold may refer to the minimum loading success rate for determiningthe count of candidate redundant devices. For example, the loadingsuccess rate threshold is 80%. The management platform may determine thecount of candidate redundant devices whose loading success rate isgreater than and/or equal to 80% as the count of candidate redundantdevices corresponding to the working device. As described in the aboveexample, the count of candidate redundant devices corresponding toworking device 4 is 2. The count of candidate redundant devicescorresponding to working device 1 is 1.

In some embodiments of the present disclosure, the management platformmay eliminate the device with high probability of failure to loadparameters among the candidate redundant devices, which can ensure thesuccessful loading of candidate redundant devices to a certain extent,and reduce the waiting time of production devices in the productionprocess.

In some embodiments, in response to that the count of candidateredundant devices corresponding to the working devices is the same, themanagement platform may determine the replacement priority of theworking devices based on the loading success rate of each candidateredundant device. For example, the management platform maypreferentially replace a working device corresponding to the candidateredundant device with a high loading success rate. For example, thecandidate redundant devices corresponding to working device 5 andworking device 6 are candidate redundant device G (loading success rate88%) and candidate redundant device H (loading success rate 95%). Themanagement platform may determine that the working device 6 is replacedin priority to the working device 5.

In some embodiments of the present disclosure, the management platformdetermines the replacement priority of working devices based on theloading success rate of each candidate redundant device. The managementplatform may ensure that the working device corresponding to thecandidate redundant device with high loading success rate is replaced inpriority, so as to reduce the waiting time of production device in theproduction process.

In some embodiments, in response to that the count of candidateredundant devices corresponding to the working devices is the same, themanagement platform may determine the priority of different workingdevices based on the upstream devices of the working devices and thepredicted loading completion time. The management platform may determinethe replacement priority of the working devices based on the priority ofdifferent working devices.

An upstream device of a working device may refer to a production deviceof a previous process adjacent to the working device. For example, inthe SMT production line, the working device is a dispensing machine, andthe upstream device of the working device is the screen printingmachine, etc. The predicted loading completion time may refer to thetime when the device completes the loading of parameters. In someembodiments, the predicted loading completion time may include a timecorresponding to the predicted loading completion time and the predictedloading duration. For example, the predicted loading time point of theworking device is 10:10, the time corresponding to the predicted loadingcompletion time is 10:11, and the predicted loading duration is 1minute.

Priority may refer to a priority level at which the working device isreplaced. There are high and low priorities. For example, the prioritymay include a first priority (highest priority), a second priority(higher priority), and the like.

In some embodiments, the management platform may set a higher priorityfor working devices with a large count of upstream devices and a shortpredicted loading completion time. The management platform maypreferentially replace the corresponding working device with the higherpriority.

In some embodiments of the present disclosure, the management platformmay preferentially replace the corresponding working device with higherpriority, which can ensure that the working device corresponding to alarge count of upstream device is replaced first, so as to reduce thewaiting time of production device in the whole production process.

In some embodiments, the management platform may obtain the confidenceof the predicted loading duration corresponding to the predicted loadingcompletion time. When the confidence of the predicted loading durationis greater than the threshold, the management platform may determine thepriority based on the predicted loading duration.

The predicted loading duration may refer to the time taken by thedevices to load parameters. The confidence of the predicted loadingduration may refer to the confidence degree of predicting the loadingduration. The confidence in predicting the loading duration may beexpressed by a value between 0 and 1. The larger the value, the morecredible the predicted loading duration is. The threshold may refer tothe lowest confidence that may be trusted to predict the loadingduration. For example, the threshold may be 0.9 or 0.95, etc. Themanagement platform may preset the threshold. The management platformmay set the threshold value according to the actual need.

In some embodiments, the management platform may obtain the confidenceof the predicted loading duration corresponding to the predicted loadingcompletion time through a prediction model. For the confidence of thepredicted loading duration corresponding to the predicted loadingcompletion time obtained through the prediction model, please refer tothe relevant description in FIG. 4 for details.

In some embodiments, the management platform may determine the priorityaccording to the predicted loading duration. The management platform maydetermine that a working device with short predicted loading durationhas higher priority. For example, the confidence of the predictedloading duration corresponding to working device 7 and working device 8is greater than the threshold (e.g., 0.9). The predicted loadingduration of working device 7 and working device 8 is 1 minute and 30seconds, respectively. The management platform may determine that thepriority of work device 8 is higher than that of work device 7.

In some embodiments of the present disclosure, when the confidence ofthe predicted loading duration is greater than the threshold, themanagement platform may determine the priority based on the predictedloading duration. The management platform may ensure the accuracy of thepredicted loading duration to a certain extent, and then ensure theaccuracy of the priority of working device, further ensure that thecorresponding working device with short predicted loading duration isreplaced first, so as to reduce the waiting time of production device inthe whole production process.

In some embodiments, the management platform may carry out thereplacement scheme through a plurality of rounds of iteration. Forexample, the management platform may determine, based on the count ofworking devices corresponding to candidate redundant devicescorresponding to a working device with the first priority, thereplacement priority of the corresponding candidate redundant devices,and then determine a target redundant device corresponding to theworking device with the first priority. The management platform mayreplace the working device of the second priority and the third priorityby repeating the above process until there is no replaceable device.

For example, the candidate redundant devices corresponding to workingdevice 9 with the first priority are A and B, and the candidateredundant devices corresponding to working device 10 with the secondpriority are B, C and D. The management platform may set that the morethe count of working devices corresponding to a candidate redundantdevice, the lower the priority of the candidate redundant device.Candidate redundant device A corresponds to one working device 9, andcandidate redundant device B corresponds to two working devices. Thepriority of candidate redundant device A is higher than that ofcandidate redundant device B. The management platform may firstdetermine that the target redundant device of the working device 9 withfirst priority is A. The management platform may then determine thetarget redundant device of the working device 10 with the secondpriority. Candidate redundant devices C and D correspond to one workingdevice 10, and candidate redundant device B corresponds to two workingdevices. The priority of candidate redundant devices C and D is higherthan that of candidate redundant device B. The management platform maydetermine that the target redundant device of working device 10 with thesecond priority is one of C or D.

In some embodiments of the present disclosure, the management platformcarries out the replacement scheme through a plurality of rounds ofiteration. The management platform may perform replacement according tothe priority of working device until there is no replaceable device,which can ensure the priority of replacement and reduce the waiting timeof production device in the whole production process.

In step 340, the management platform sends a replacement instruction tothe working device in the object platform and its corresponding targetredundant device based on the replacement scheme.

The replacement instruction may refer to an instruction on how toreplace between devices. The replacement instruction may includereplacement time, replaceable target redundant device corresponding todifferent working device, etc. In some embodiments, the replacementinstruction may be a classification control instruction, and differenttypes of working devices correspond to different replacementinstructions. For example, different types of work devices havedifferent replacement time. The replacement instructions correspondingto a plurality of working devices of the same type are also different.For example, the replacement time corresponding to working devices withdifferent priorities is different.

In some embodiments, the management platform may send differentreplacement instructions to different working devices in the objectplatform and their corresponding target redundant devices based on thereplacement scheme. For example, the management platform may send areplacement instruction (replacement time 10:10, etc.) to the workingdevice 9 and the target redundant device A.

In some embodiments, if there is a device that has not been replaced inthe working device, the management platform may send an instructiondirectly to load and produce a new product. For example, in theproduction line, there are five working devices and three redundantdevices, three redundant devices have been replaced, and two of theworking devices have not been replaced, and the management platform maysend the instruction of directly loading parameters of producing newproducts to the two working devices that have not been replaced. The twoworking devices may directly load the parameters of producing newproducts for production.

In some embodiments, when the replacement of the working device and thetarget redundant device is completed, the target redundant devicebecomes the working device, and the original working device becomes theredundant device.

In some embodiments of the present disclosure, when the managementplatform receives the instruction to produce new products, it maydetermine the replacement scheme based on the matching relationshipbetween redundant devices and working devices. The management platformmay ensure that redundant device may replace working device in timethrough the above methods, reducing the waiting time of productiondevice in the production process, so as to ensure that the productionline may be put into production as soon as possible.

FIG. 4 is a flowchart illustrating an exemplary process for determininga loading plan and sending a loading instruction by a sensor networkplatform according to some embodiments of the present disclosure. Asshown in FIG. 4 , the process 400 includes the following steps. In someembodiments, process 400 may be performed by a sensor network platform.

In step 410, the sensor network platform predicts a predicted loadingtime of the parameters of each type of production devices for producingnew products.

The predicted loading time may refer to the estimated time when thedevice loads the production parameters of new products. The predictedloading time is different for different production devices. Thepredicted loading time may include the start time point of loading andthe predicted loading duration, etc. The start time point of loading mayrefer to the time when the device starts loading. The predicted loadingduration may refer to a time period when the device is loading, forexample, 30 seconds, 1 minute, etc.

In some embodiments, the sensor network platform may predict thepredicted loading time of the parameters for each type of productiondevices for production of the new product. For example, the sensornetwork platform may predict the predicted loading time of each type ofproduction devices according to the device type of each type ofproduction devices and the production requirements of the plannedproduct.

In some embodiments, the sensor network platform may process the type ofproduction device and the production requirements of planned productsbased on the prediction model to determine the predicted loadingduration of each type of production devices.

The prediction model refers to a model that may predict the loadingduration. In some embodiments, the type of prediction model may includeneural network model, deep neural network, etc., and the selection ofmodel type may depend on the specific situation. In some embodiments,the input of the prediction model may include the device type of eachtype of production devices, the production requirements of the plannedproducts, etc. The production requirements of planned products may referto the requirements for the production of new products. Different newproducts have different production requirements. The count of productionparameters of new products may affect the loading time. The output ofthe prediction model may include the predicted loading duration of eachtype production device.

In some embodiments, the input of the prediction model may also includethe actual loading time of other production devices that have loaded,etc. The actual loading time may refer to the actual loading time of thedevice, for example, 40 seconds, 65 seconds, etc. In some embodiments,the input of the prediction model may be dynamically updated. Forexample, when a production device has completed the parameter loading ofnew product production, the sensor network platform may input the actualloading duration of other production devices that have loaded into theprediction model.

In some embodiments, the output of the prediction model may includeconfidence of the predicted loading duration. The more data on theactual loading duration of other production devices that have loaded theparameters, the higher the confidence of the predicted loading durationof each type of production devices output by the prediction model. Thehigher the confidence of the predicted loading duration, the morecredible the predicted loading duration of the production device outputby the prediction model.

In some embodiments, the sensor network platform may input the type ofproduction device, the production requirements of planned products, andthe actual loading duration of other production devices that have loadedinto the prediction model. The prediction model outputs the predictedloading duration and the confidence of the predicted loading duration ofeach type of production devices.

In some embodiments, a prediction model may be obtained based on aplurality of training samples and label training.

In some embodiments, a training sample includes the type of sampleproduction device, the production requirements of the sample productsplanned to be produced, the actual loading duration of other sampleproduction devices have loaded, etc. The label is the predicted loadingduration of each type of sample production devices. Training data may beobtained based on historical data. The label of training data may bedetermined by manual annotation or automatic annotation. For example,the sensor network platform may perform automatic annotation bydetermining the actual loading time of each type of production devicesaccording to the historical data.

In some embodiments, the sensor network platform may improve theconfidence of the predicted loading duration of each type of productiondevices output by the prediction model by increasing the data of theactual loading duration of other production devices that have loaded. Insome embodiments, the sensor network platform may preset a confidencethreshold, such as 0.9. When the confidence is greater than or equal to0.9, the sensor network platform may take the predicted loading durationoutput by the prediction model as the loading duration of a redundantdevice, and update the parameters for production.

In some embodiments of the present disclosure, the sensor networkplatform determines the predicted loading duration of each type ofproduction devices through the prediction model. Through the abovemethod, the accuracy of predicting the loading duration may be improved.The sensor network platform inputs the actual loading duration of otherproduction devices that have loaded into the prediction model. Theactual loading duration of other production devices that have loaded hasreference significance for the predicted loading duration of the devicesto load the parameters for new product production. Dynamically updatingthe actual loading duration of other production devices may improve theconfidence of the prediction model in the prediction results of thepredicted loading duration, in order to reduce the waiting time ofproduction device in the production process, so as to ensure that theproduction line can be put into production as soon as possible.

In step 420, the sensor network platform determines a loading plan of aredundant device based on the predicted loading time.

The loading plan of the redundant device may refer to the plan of howthe redundant device loads parameters. In some embodiments, the loadingplan of the redundant device includes the start time point of theloading of each device in each type of production devices. In someembodiments, the start time point of loading of all redundant devicesmay be the same. For example, the sensor network platform may take thepreset time point before the end of production of all current productsas the start time point of the loading. The start time point may bedetermined based on the maximum predicted loading duration. For example,the maximum predicted loading duration in a production device is 5minutes, the production end time of all current products is 11:50, andthe sensor network platform may determine 11:45 as the start time pointof the loading.

In some embodiments, start time points of the loading of differentredundant devices may be different. For example, the preset time pointbefore the end of the production of the current product by a productiondevice is used as start time point of the loading of the productiondevice. The sensor network platform may determine the start time pointof the loading based on the predicted loading duration of the device.For example, the predicted loading duration of production device A is 2minutes, and the end time of the current product production is 11:48.The sensor network platform may determine 11:46 as the start time pointof the loading of the production device A.

In step 430, the sensor network platform sends a loading instruction tothe redundant device of the object platform based on the loading plan.

Redundant instruction refers to the instruction related to the loadingcontrol device. Loading instructions may include parameters ofproduction of new products and the start time point of loading. In someembodiments, the sensor network platform may send loading instructionsto redundant devices of the object platform based on the loading plan.For example, a loading instruction sent by the sensor network platformto the production device A is that the start time point of the loadingis 11:46, and the parameter of new product production is parameter 1.

Through the above methods, the sensor network platform may ensure thatall redundant devices complete loading parameters of the production ofnew products before the replacement of the working device and targetredundant device, thereby reducing the waiting time of production devicein the production process, so as to ensure that the production line maybe put into production as soon as possible.

In some embodiments, the sensor network platform may include a pluralityof sensor network sub-platforms. Each sensor network sub-platform of aplurality of sensor network sub-platforms may correspond to each type ofthe production devices. Each sensor network sub-platform may be used tocontrol the parameter loading of the corresponding production device.

The sensor network sub-platform and the object sub-platform may beconfigured with special information channel and gateway. Through theinformation channel and gateway, control instructions may be sent tocontrol the production device, such as parameters loading, accessing,startup and shutdown of the production device. For example, the sensornetwork platform includes three sensor network sub-platforms: sensornetwork sub-platform 1, sensor network sub-platform 2 and sensor networksub-platform 3. The sensor network sub-platform 1 may be used to controlthe production device A. The sensor network sub-platform 2 may be usedto control the production device B. The sensor network sub-platform 3may be used to control the production device C.

In some embodiments, the object platform may include a plurality ofobject sub-platforms. Each object sub-platform of a plurality of objectsub-platforms may correspond to each type of production devices. Forexample, in the SMT production line, a plurality of types of productiondevices may include screen printing machine, dispensing machine, patchmachine, curing machine, reflow soldering machine, etc. A plurality ofobject sub-platforms of the object platform may include screen printingmachine-object sub-platform, dispensing machine-object sub-platform,patch machine-object sub-platform, curing machine-object sub-platform,reflow soldering machine-object sub-platform, etc.

Those skilled in the art can realize that the units and algorithm stepsof each example described in combination with the embodiments disclosedherein may be realized by electronic hardware, computer software or acombination of the two. In order to clearly illustrate theinterchangeability of hardware and software, the composition and stepsof each example have been generally described according to function inthe above description. Whether these functions are performed in hardwareor software depends on the specific application and design constraintsof the technical scheme. Professional technicians may use differentmethods to realize the described functions for each specificapplication, but this realization should not be considered beyond thescope of the present disclosure.

In several embodiments provided in the present disclosure, it should beunderstood that the disclosed devices and methods can be realized inother ways. For example, the device embodiment described above is onlyschematic. For example, the division of the unit is only a logicalfunction division, and there may be another division mode in actualimplementation. For example, a plurality of units or components may becombined or integrated into another system, or some features may beignored or not executed. In addition, the mutual coupling or directcoupling or communication connection shown or discussed may be indirectcoupling or communication connection through some interfaces, devices orunits, or electrical, mechanical or other forms of connection.

The unit described as a separate part may or may not be physicallyseparated. As a unit, those skilled in the art may realize that the unitand algorithm steps of each example described in combination with theembodiments disclosed herein may be realized by electronic hardware,computer software or a combination of the two. In order to clearlyillustrate the interchangeability of hardware and software. In the abovedescription, the composition and steps of each example have beengenerally described according to the function. Whether these functionsare performed in hardware or software depends on the specificapplication and design constraints of the technical scheme. Professionaltechnicians may use different methods to realize the described functionsfor each specific application, but this realization should not beconsidered beyond the scope of the present disclosure.

In addition, each functional unit in each embodiment of the presentdisclosure may be integrated into one processing unit, each unit mayexist separately, or two or more units may be integrated into one unit.The above integrated units may be realized in the form of hardware orsoftware functional units.

If the integrated unit is realized in the form of software functionalunit and sold or used as an independent product, it may be stored in acomputer-readable storage medium. Based on this understanding, thetechnical solution of the present disclosure is essentially or part ofthe contribution to the prior art, or all or part of the technicalsolution may be embodied in the form of software product, which isstored in a storage medium. It includes several instructions to enable acomputer device (which may be a personal computer, server, grid device,etc.) to perform all or part of the steps of the method described ineach embodiment of the present disclosure. The aforementioned storagemedia include: USB flash disk, mobile hard disk, read only memory (ROM),random access memory (RAM), magnetic disc or optical disc and othermedia that may store program code.

The specific embodiments described above further detail the purpose,technical scheme and beneficial effects of the present disclosure. Itshould be understood that the above are only the specific embodiments ofthe present disclosure and are not used to limit the scope of protectionof the present disclosure. Any modification, equivalent replacement,improvement, etc. made within the spirit and principles of the presentdisclosure should be included in the scope of protection of the presentdisclosure.

What is claimed is:
 1. An industrial internet of things system forautomatic replacement of production line production devices, comprising:a user platform, a service platform, a management platform, a sensornetwork platform, and an object platform that interact in turn, whereinthe user platform is configured as a terminal device and interacts witha user; the service platform is configured as a first server, receivesan instruction of the user platform and sends it to the managementplatform, extracts information required for processing the user platformfrom the management platform, and sends the information to the userplatform; the management platform is configured as a second server,controls the operation of the object platform, and receives feedbackdata from the object platform; the sensor network platform is configuredas a communication network and a gateway for the interaction between theobject platform and the management platform; the object platform isconfigured as production line devices, the production line devicesincluding a plurality types of production devices arranged in a presetorder, each of the plurality types of production devices including aplurality of working devices and at least one redundant device; thesecond server determines, based on a matching relationship between theat least one redundant device and the working devices, replaceablecandidate redundant devices corresponding to the working devices whenreceiving an instruction for producing a new product transmitted by thefirst server, and determines a replacement scheme based on thereplaceable candidate redundant devices, wherein the instruction isobtained from the terminal and the replacement scheme includingreplaceable target redundant devices corresponding to the workingdevices; the second server generates a replacement instruction based onthe replacement scheme, and sends the replacement instruction to theworking devices and the corresponding target redundant devices of theobject platform.
 2. The industrial internet of things system accordingto claim 1, wherein to determine the replacement scheme, the secondserver is further configured to: determine a count of the candidateredundant devices corresponding to the working devices; determine areplacement priority of the working devices based on the count of thecandidate redundant devices corresponding to the working devices; anddetermine the replacement scheme based on the replacement priority. 3.The industrial internet of things system according to claim 2, whereinto determine a count of the candidate redundant devices corresponding tothe working devices, the second server is further configured todetermine the count of candidate redundant devices by taking loadingsuccess rates of the candidate redundant devices as a weight andperforming weighted summation.
 4. The industrial internet of thingssystem according to claim 2, wherein to determine a replacement priorityof the working devices, the second server is further configured todetermine the replacement priority of the working devices based on theloading success rates of the candidate redundant devices when the countof the candidate redundant devices corresponding to the working devicesis the same.
 5. The industrial internet of things system according toclaim 2, wherein to determine a replacement priority of the workingdevices, the second server is further configured to determine thereplacement priority of the working devices based on an upstream deviceand a predicted loading completion time of each of the working deviceswhen the count of the candidate redundant devices corresponding to theworking devices is the same, wherein the predicted loading completiontime is a prediction time for a type of production devices correspondingto each of the working devices to load production parameters of the newproduct.
 6. The industrial internet of things system according to claim5, wherein to determine a replacement priority of the working devices,the second server is further configured to: obtain a confidence of apredicted loading duration corresponding to the predicted loadingcompletion time of each of the working devices; and in response to thepredicted loading duration is greater than a threshold, determine thereplacement priority based on the predicted loading duration.
 7. Theindustrial internet of things system according to claim 1, wherein thesensor network platform is configured to: predict a predicted loadingtime of parameters of producing a new product by each type of productiondevices; determine a loading plan of the at least one redundant devicebased on the predicted loading time, the loading plan including aloading start time point of the target redundant devices of each type ofproduction devices; and send a loading instruction to the targetredundant devices of the object platform based on the loading plan. 8.The industrial internet of things system according to claim 7, whereinto predict a predicted loading time of parameters of producing a newproduct by each type of production devices, the sensor network platformis further configured to: determine the predicted loading durationcorresponding to predicted loading time of each type of productiondevices by processing the type of production devices and productionrequirements of the planning new product based on a prediction model,the prediction model being a neural network model.
 9. The industrialinternet of things system according to claim 8, wherein to predict apredicted loading time of parameters of producing a new product by eachtype of production devices, the sensor network platform is furtherconfigured to: determine the predicted loading duration corresponding topredicted loading time of each type of production devices and confidenceby processing the type of production devices, the productionrequirements of the planning new product, and actual loading durationsof other production devices that have loaded based on the predictionmodel.
 10. The industrial internet of things system according to claim1, wherein the sensor network platform comprises a plurality of sensornetwork sub-platforms, the plurality of sensor network sub-platformscorresponds to the plurality types of production devices, and theplurality of sensor network sub-platforms is used to control theparameter loading of the corresponding production devices, respectively.11. The industrial internet of things system according to claim 1,wherein the object platform comprises a plurality of objectsub-platforms, and the plurality of object sub-platforms corresponds toof the plurality types of production devices, respectively.
 12. Acontrol method for an industrial internet of things system for automaticreplacement of production line production devices, applied to a userplatform, a service platform, a management platform, a sensor networkplatform, and an object platform that interact in turn, wherein the userplatform is configured as a terminal device and interacts with a user;the service platform is configured as a first server, receives aninstruction of the user platform and sends it to the managementplatform, extracts information required for processing the user platformfrom the management platform, and sends the information to the userplatform; the management platform is configured as a second server,controls the operation of the object platform, and receives feedbackdata from the object platform; the sensor network platform is configuredas a communication network and a gateway for the interaction between theobject platform and the management platform; the object platform isconfigured as production line devices, the production line devicesincluding a plurality types of production devices arranged in a presetorder, each of the plurality types of production devices including aplurality of working devices and at least one redundant device; thecontrol method comprises: determining, by the second server, replaceablecandidate redundant devices corresponding to the working devices basedon a matching relationship between the at least one redundant device andthe working devices when receiving an instruction for producing a newproduct transmitted by the first server, and determining a replacementscheme based on the replaceable candidate redundant devices, wherein theinstruction is obtained from the terminal and the replacement schemeincluding replaceable target redundant devices corresponding to theworking devices; generating, by the second server, a replacementinstruction based on the replacement scheme, and sends the replacementinstruction to the working devices and the corresponding targetredundant devices of the object platform.
 13. The control methodaccording to claim 12, wherein the determining the replacement schemeincludes: determining a count of the candidate redundant devicescorresponding to the working devices; determining a replacement priorityof the working devices based on the count of the candidate redundantdevices corresponding to the working devices; and determining thereplacement scheme based on the replacement priority.
 14. The controlmethod according to claim 13, wherein the determining a count of thecandidate redundant devices corresponding to the working devicesincludes: determining the count of candidate redundant devices by takingloading success rates of the candidate redundant devices as a weight andperforming weighted summation.
 15. The control method according to claim13, wherein the determining a replacement priority of the workingdevices includes determining the replacement priority of the workingdevices based on the loading success rates of the candidate redundantdevices when the count of the candidate redundant devices correspondingto the working devices is the same.
 16. The control method according toclaim 13, wherein the determining a replacement priority of the workingdevices includes determining the replacement priority of the workingdevices based on an upstream device and a predicted loading completiontime of each of the working devices when the count of the candidateredundant devices corresponding to the working devices is the same,wherein the predicted loading completion time is a prediction time for atype of production devices corresponding to each of the working devicesto load production parameters of the new product.
 17. The control methodaccording to claim 16, wherein the determining a replacement priority ofthe working devices includes: obtaining a confidence of a predictedloading duration corresponding to the predicted loading completion timeof each of the working devices; and in response to the predicted loadingduration is greater than a threshold, determining the replacementpriority based on the predicted loading duration.
 18. The control methodaccording to claim 12, further comprising: by the sensor networkplatform, predicting a predicted loading time of parameters of producinga new product by each type of production devices; determining a loadingplan of the at least one redundant device based on the predicted loadingtime, the loading plan including a loading start time point of thetarget redundant devices of each type of production devices; and sendinga loading instruction to the target redundant devices of the objectplatform based on the loading plan.
 19. The control method according toclaim 18, wherein the predicting a predicted loading time of parametersof producing a new product by each type of production devices includes:determining the predicted loading duration corresponding to predictedloading time of each type of production devices by processing the typeof production devices and production requirements of the planning newproduct based on a prediction model, the prediction model being a neuralnetwork model.
 20. The control method according to claim 19, wherein thepredicting a predicted loading time of parameters of producing a newproduct by each type of production devices includes: determining thepredicted loading duration corresponding to predicted loading time ofeach type of production devices and confidence by processing the type ofproduction devices, the production requirements of the planning newproduct, and actual loading durations of other production devices thathave loaded based on the prediction model.